Adaptive detection for a differential chaos-based multiple access system on unknown multipath fading channels

This paper addresses the problem of bit detection for a chaos-based multiple-access system. In particular, one considers the Differential Chaos Shift Keying modulation. It is assumed that the transmission channels are frequency-selective. Moreover, the channel coefficients and the channel delays are unknown to the receiver. It is only assumed that vague estimates of the minimum and maximum channel delays are available for the user of interest. In this context, the detection is achieved using a training sequence from which an LMS detector is derived. The theoretical performance results are compared to those of the optimal detector for which all channel characteristics are known. Simulation results are given, which confirm the theoretical study

Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services

Low-power wireless communication is a central building block of Cyber-physical Systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude the paper with a discussion on open research questions in this field.Comment: Submitted to ACM Computing Survey

Collaborative, Intelligent, and Adaptive Systems for the Low-Power Internet of Things

With the emergence of the Internet of Things (IoT), more and more devices are getting equipped with communication capabilities, often via wireless radios. Their deployments pave the way for new and mission-critical applications: cars will communicate with nearby vehicles to coordinate at intersections; industrial wireless closed-loop systems will improve operational safety in factories; while swarms of drones will coordinate to plan collision-free trajectories. To achieve these goals, IoT devices will need to communicate, coordinate, and collaborate over the wireless medium. However, these envisioned applications necessitate new characteristics that current solutions and protocols cannot fulfill: IoT devices require consistency guarantees from their communication and demand for adaptive behavior in complex and dynamic environments.In this thesis, we design, implement, and evaluate systems and mechanisms to enable safe coordination and adaptivity for the smallest IoT devices. To ensure consistent coordination, we bring fault-tolerant consensus to low-power wireless communication and introduce Wireless Paxos, a flavor of the Paxos algorithm specifically tailored to low-power IoT. We then present STARC, a wireless coordination mechanism for intersection management combining commit semantics with synchronous transmissions. To enable adaptivity in the wireless networking stack, we introduce Dimmer and eAFH. Dimmer combines Reinforcement Learning and Multi-Armed Bandits to adapt its communication parameters and counteract the adverse effects of wireless interference at runtime while optimizing energy consumption in normal conditions. eAFH provides dynamic channel management in Bluetooth Low Energy by excluding and dynamically re-including channels in scenarios with mobility. Finally, we demonstrate with BlueSeer that a device can classify its environment, i.e., recognize whether it is located in a home, office, street, or transport, solely from received Bluetooth Low Energy signals fed into an embedded machine learning model. BlueSeer therefore increases the intelligence of the smallest IoT devices, allowing them to adapt their behaviors to their current surroundings

Multi user chaotic communication systems sing orthogonal chaotic vectors

Due to quasi orthogonal nature of chaotic spreading sequences, the co-channel interference will be introduced and increases with the increase in number of users and limits the number of simultaneous users transmitting information. In this dissertation the application of orthogonal chaotic vector (OCV) for spreading information bits is presented. The bit error rate of the multi user chaotic communication system is analysed through simulation and analytical expressions. Two main types of communication scenarios are considered, multi user chaotic communication system with coherent receiver and training assisted non coherent multi user chaotic communication system with adaptive receiver. The first case deals with ideal scenario where it is assumed that exact replica of chaotic vector used to spread data is available at the receiver and the information is extracted without synchronisation error. Thus lacks practical realisation but, the results obtained will provide a lower bound for comparison with other practical counter parts. The second scenario deals with more practical approach where a reference chaotic sequence is also transmitted by modulating with training bits so that the chaotic vector required for correlation can be recovered at the receiver

Synchronous and Concurrent Transmissions for Consensus in Low-Power Wireless

With the emergence of the Internet of Things, autonomous vehicles and the Industry 4.0, the need for dependable yet adaptive network protocols is arising. Many of these applications build their operations on distributed consensus. For example, UAVs agree on maneuvers to execute, and industrial systems agree on set-points for actuators.Moreover, such scenarios imply a dynamic network topology due to mobility and interference, for example. Many applications are mission- and safety-critical, too.Failures could cost lives or precipitate economic losses.In this thesis, we design, implement and evaluate network protocols as a step towards enabling a low-power, adaptive and dependable ubiquitous networking that enables consensus in the Internet of Things. We make four main contributions:- We introduce Orchestra that addresses the challenge of bringing TSCH (Time Slotted Channel Hopping) to dynamic networks as envisioned in the Internet of Things. In Orchestra, nodes autonomously compute their local schedules and update automatically as the topology evolves without signaling overhead. Besides, it does not require a central or distributed scheduler. Instead, it relies on the existing network stack information to maintain the schedules.- We present A2 : Agreement in the Air, a system that brings distributed consensus to low-power multihop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this layer and enables the two- and three-phase commit protocols, and services such as group membership, hopping sequence distribution, and re-keying.- We present Wireless Paxos, a fault-tolerant, network-wide consensus primitive for low-power wireless networks. It is a new variant of Paxos, a widely used consensus protocol, and is specifically designed to tackle the challenges of low-power wireless networks. By utilizing concurrent transmissions, it provides a dependable low-latency consensus.- We present BlueFlood, a protocol that adapts concurrent transmissions to Bluetooth. The result is fast and efficient data dissemination in multihop Bluetooth networks. Moreover, BlueFlood floods can be reliably received by off-the-shelf Bluetooth devices such as smartphones, opening new applications of concurrent transmissions and seamless integration with existing technologies

Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community

Multiuser detection employing recurrent neural networks for DS-CDMA systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.Over the last decade, access to personal wireless communication networks has evolved to a point of necessity. Attached to the phenomenal growth of the telecommunications industry in recent times is an escalating demand for higher data rates and efficient spectrum utilization. This demand is fuelling the advancement of third generation (3G), as well as future, wireless networks. Current 3G technologies are adding a dimension of mobility to services that have become an integral part of modem everyday life. Wideband code division multiple access (WCDMA) is the standardized multiple access scheme for 3G Universal Mobile Telecommunication System (UMTS). As an air interface solution, CDMA has received considerable interest over the past two decades and a great deal of current research is concerned with improving the application of CDMA in 3G systems. A factoring component of CDMA is multiuser detection (MUD), which is aimed at enhancing system capacity and performance, by optimally demodulating multiple interfering signals that overlap in time and frequency. This is a major research problem in multipoint-to-point communications. Due to the complexity associated with optimal maximum likelihood detection, many different sub-optimal solutions have been proposed. This focus of this dissertation is the application of neural networks for MUD, in a direct sequence CDMA (DS-CDMA) system. Specifically, it explores how the Hopfield recurrent neural network (RNN) can be employed to give yet another suboptimal solution to the optimization problem of MUD. There is great scope for neural networks in fields encompassing communications. This is primarily attributed to their non-linearity, adaptivity and key function as data classifiers. In the context of optimum multiuser detection, neural networks have been successfully employed to solve similar combinatorial optimization problems. The concepts of CDMA and MUD are discussed. The use of a vector-valued transmission model for DS-CDMA is illustrated, and common linear sub-optimal MUD schemes, as well as the maximum likelihood criterion, are reviewed. The performance of these sub-optimal MUD schemes is demonstrated. The Hopfield neural network (HNN) for combinatorial optimization is discussed. Basic concepts and techniques related to the field of statistical mechanics are introduced and it is shown how they may be employed to analyze neural classification. Stochastic techniques are considered in the context of improving the performance of the HNN. A neural-based receiver, which employs a stochastic HNN and a simulated annealing technique, is proposed. Its performance is analyzed in a communication channel that is affected by additive white Gaussian noise (AWGN) by way of simulation. The performance of the proposed scheme is compared to that of the single-user matched filter, linear decorrelating and minimum mean-square error detectors, as well as the classical HNN and the stochastic Hopfield network (SHN) detectors. Concluding, the feasibility of neural networks (in this case the HNN) for MUD in a DS-CDMA system is explored by quantifying the relative performance of the proposed model using simulation results and in view of implementation issues

Power control for WCDMA

This project tries to introduce itself in the physical implementations that make possible the denominated third generation mobile technology. As well as to know the technology kind that makes possible, for example, a video-call in real time. During this project, the different phases passed from the election of WCDMA like the access method for UMTS will appear. Its coexistence with previous network GSM will be analyzed, where the compatibility between systems has been one of the most important aspects in the development of WCDMA, the involved standardization organisms in the process, as well as the different protocols that make the mobile communications within a network UTRAN possible. Special emphasis during the study of the great contribution that has offered WCDMA with respect to the control of power of the existing signals will be made. The future lines that are considered in the present, and other comment that already are in their last phase of development in the field of the mobile technology. UMTS through WCDMA can be summarized like a revolution of the air interface accompanied by a revolution in the network of their architecture